Reliable propagation of slow-modulations of the firing rate across multiple layers of a feedforward network (FFN) has proven difficult to capture in spiking neural models. In this paper, we explore necessary conditions for reliable and stable propagation of time-varying asynchronous spikes whose instantaneous rate of changes—in fairly short time windows [20–100] msec—represents information of slow fluctuations of the stimulus. Specifically, we study the effect of network size, level of background synaptic noise, and the variability of synaptic delays in an FFN with all-to-all connectivity. We show that network size and the level of background synaptic noise, together with the strength of synapses, are substantial factors enabling the propagation of asynchronous spikes in deep layers of an FFN. In contrast, the variability of synaptic delays has a minor effect on signal propagation.

中文翻译：

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慢时变射速可靠传播的必要条件

事实证明，在尖峰神经模型中很难在前馈网络 (FFN) 的多层中可靠地传播发射率的缓慢调制。在本文中，我们探索了可靠和稳定传播时变异步尖峰的必要条件，其瞬时变化率 - 在相当短的时间窗口 [20-100] 毫秒内 - 代表刺激缓慢波动的信息。具体来说，我们研究了网络大小、背景突触噪声水平以及具有全对全连接的 FFN 中突触延迟的可变性的影响。我们表明，网络大小和背景突触噪声的水平，以及突触的强度，是能够在 FFN 的深层传播异步尖峰的重要因素。相比之下，